Systems and methods for measuring physiological parameters

ABSTRACT

A device for detecting physiological parameters is used to detect a degree of user hypoxemia in response to flight conditions; degree of hypoxemia may be used automatically to modify actions by a training device such as a reduced oxygen breathing device or centrifuge and generate feedback or modifications to training profiles for future use. Machine learning processes may be combined with sensor activity to discover relationships between maneuvers, environmental conditions, physiological parameters, and degrees of impairment to develop optimal flight or training plans.

RELATED APPLICATION DATA

This application is a continuation in part of U.S. nonprovisional patentapplication Ser. No. 16/012,713, filed on Jun. 19, 2018, and titled“SYSTEMS AND METHODS FOR MEASURING PHYSIOLOGICAL PARAMETERS”, which is acontinuation in part of U.S. nonprovisional patent application Ser. No.15/492,612, filed on Apr. 20, 2017, and titled “HUMAN PERFORMANCE OXYGENSENSOR.” Each of U.S. nonprovisional patent application Ser. No.16/012,713 and U.S. nonprovisional patent application Ser. No.15/492,612 is incorporated herein by reference in its entirety.

FIELD OF THE INVENTION

This invention relates to physiological sensing devices, and inparticular to systems and methods for measuring physiologicalparameters.

BACKGROUND

Blood oxygen saturation can determine a plurality of physicalcharacteristics and ailments, including determining whether anindividual is on the verge of losing consciousness. Typically, sensorsmeasuring oxygenation are placed on the fingers or foreheads of patientsand do not include a means of analyzing the data and alerting the useror a third party of whether an issue has been determined.

SUMMARY OF THE DISCLOSURE

According to an aspect, a device for training pilots using physiologicalsensor feedback for flight circumstances that cause hypoxemia, includesa housing configured to be mounted to an exterior body surface of auser. The device includes at least a physiological sensor attached tothe housing and configured to detect at least a physiological parameterassociated with hypoxemia. The device includes a training and feedbackprocessor in communication with the at least a physiological sensor. Thetraining and feedback processor is designed and configured to detect atleast a flight condition having a causative association with hypoxemia,measure, using the at least a physiological sensor, at least aphysiological parameter associated with hypoxemia, and determine, by thetraining and feedback processor, and based on the at least aphysiological parameter, a degree of pilot hypoxemia. The deviceincludes a user signaling device in communication with the training andfeedback processor, the user signaling device configured to indicate thedegree of pilot hypoxemia to at least a user.

In another aspect, a method of training pilots using physiologicalsensor feedback for flight circumstances that cause hypoxemia includesmounting a device for physiological sensor feedback to a user, thedevice further including a housing, at least a physiological sensorattached to the housing and configured to detect at least aphysiological parameter associated with hypoxemia, and a training andfeedback processor in communication with the at least a physiologicalsensor. The method includes detecting, by the training and feedbackprocessor, at least a flight condition having a causative associationwith hypoxemia. The method includes measuring, using the at least aphysiological sensor at least a physiological parameter associated withhypoxemia. The method includes determining, by the training and feedbackprocessor, and based on the at least a physiological parameter, a degreeof pilot hypoxemia. The method includes indicating, using a usersignaling device, the degree of pilot hypoxemia to at least a user.

These and other aspects and features of non-limiting embodiments of thepresent invention will become apparent to those skilled in the art uponreview of the following description of specific non-limiting embodimentsof the invention in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

For the purpose of illustrating the invention, the drawings show aspectsof one or more embodiments of the invention. However, it should beunderstood that the present invention is not limited to the precisearrangements and instrumentalities shown in the drawings, wherein:

FIG. 1 shows a perspective view of a device according to an embodimentdisclosed herein;

FIG. 2 shows a front view of a device according to an embodimentdisclosed herein;

FIG. 3 shows a side view of a device according to an embodimentdisclosed herein;

FIG. 4 shows a perspective view of a device according to an embodimentdisclosed herein;

FIG. 5 shows a front sectional view of a device according to anembodiment disclosed herein;

FIG. 6 is a schematic illustration of an exemplary embodiment of anear-infrared spectroscopy sensor;

FIG. 7 is a schematic diagram of some aspects of user cranial anatomy inan embodiment;

FIG. 8 shows a flowchart of a method of using the human performanceoxygen sensor according to an embodiment of the present invention;

FIG. 9 illustrates a block diagram of an embodiment of a systemincorporating a device according to an embodiment;

FIG. 10 is a flow diagram of an exemplary embodiment of a method oftraining pilots using physiological sensor feedback; and

FIG. 11 is a block diagram of a computing system that can be used toimplement any one or more of the methodologies disclosed herein and anyone or more portions thereof.

DETAILED DESCRIPTION

In an embodiment, devices and methods disclosed herein enable a systemto detect physiological parameters such as blood oxygen level, bloodpressure, and heart rate of a user through nonintrusive means. Sensorsmounted in optimal locations on the head or neck of the user may detectphysiological parameters accurately, minimizing interference inactivities the user engages in while obtaining a clearer signal thanotherwise would be possible. Embodiments of the disclosed device mayprovide users such as pilots, firemen, and divers who are operatingunder extreme circumstances with an early warning regarding potentialcrises such as loss of consciousness, affording the user a few preciousextra seconds to avert disaster. Alarms may be provided to the user viabone-conducting transducers or by integration into displays the user isoperating, increasing the likelihood that the user will notice thewarning in time. Embodiments of devices, systems, and methods herein mayenable training for pilots or other persons to function withinphysiological limitations imposed by their environment, such ashypoxemia imposed by altitude, high G forces and the like; training mayfurther enable users to learn how to avoid total impairment, and tofunction under partial impairment.

Referring now to FIGS. 1-5, an exemplary embodiment of a perspectiveview (FIG. 1), a side view (FIG. 2), a front view (FIG. 3), aperspective view (FIG. 4), and a front sectional view (FIG. 5) of adevice for measuring physiological parameters 100 is illustrated.Referring now to FIG. 1, device for measuring physiological parameters100 includes a housing 104. Housing 104 may be mounted to an exteriorbody surface of a user; exterior body surface may include, withoutlimitation, skin, nails such as fingernails or toenails, hair, aninterior surface of an orifice such as the mouth, nose, or ears, or thelike. A locus on exterior body surface for mounting of housing 104and/or other components of device may be selected for particularpurposes as described in further detail below. Exterior body surfaceand/or locus may include an exterior body surface of user's head, face,or neck. Housing 104 may be constructed of any material or combinationof materials, including without limitation metals, polymer materialssuch as plastics, wood, fiberglass, carbon fiber, or the like. Housing104 may include an outer shell 108. Outer shell 108 may, for instance,protect elements of device 100 from damage, and maintain them in acorrect position on a user's body as described in further detail below.Housing 104 and/or outer shell 108 may be shaped, formed, or configuredto be inserted between a helmet worn on a head of the user and theexterior body surface; housing 104 and/or outer shell 108 may be shapedto fit between the helmet and the exterior body surface. As anon-limiting example, exterior body surface may be a surface, such as asurface of the head, face, or neck of user, which is wholly or partiallycovered by helmet, as described for example in further detail below. Asa further non-limiting example, housing 104 may be formed to have asimilar or identical shape to a standard-issue “ear cup” incorporated inan aviation helmet, so that housing 104 can replace ear cup after earcup has been removed; in an embodiment, device 100 may incorporate oneor more elements of ear-cup, including sound-dampening properties, oneor more speakers or other elements typically used to emit audio signalsin headsets or headphones, or the like. As a non-limiting example,device 100, housing 104, and/or shell may form a form-fit replacementfor standard earcups found in military flight helmets. Shell may berigid, where “rigid” is understood as having properties of an exteriorcasing typically used in an earcup, over-ear headphone, hearingprotection ear covering, or the like; materials used for such a shellmay include, without limitation, rigid plastics such as polycarbonateshell plastics typically used in helmets and hardhats, metals such assteel, and the like. Persons skilled in the art, upon reading theentirety of this disclosure, will understand “rigid” in this context assignifying sufficient resistance to shear forces, deformations, andimpacts to protect electronic components as generally required fordevices of this nature.

Still viewing FIGS. 1-5, housing 104 may include a seal 112 that restsagainst exterior body surface when housing 104 is mounted thereon. Seal112 may be pliable; seal 112 may be constructed of elastomeric, elastic,or flexible materials including without limitation flexible,elastomeric, or elastic rubber, plastic, silicone including medicalgrade silicone, gel, and the like. Pliable seal 112 may include anycombination of materials demonstrating flexible, elastomeric, or elasticproperties, including without limitation foams covered with flexiblemembranes or sheets of polymer, leather, or textile material. As anon-limiting example, pliable seal 112 may include any suitable pliablematerial for a skin-contacting seal portion of an earcup or other deviceconfigured for placement over a user's ear, including without limitationany pliable material or combination of materials suitable for use onheadphones, headsets, earbuds, or the like. In an embodiment, pliableseal 112 advantageously aids in maintaining housing 104 and/or othercomponents of device 100 against exterior body surface; for instance,where exterior body surface has elastomeric properties and may beexpected to flex, stretch, or otherwise alter its shape or position toduring operation, pliable seal 112 may also stretch, flex, or otherwisealter its shape similarly under similar conditions, which may have theeffect of maintaining seal 112 and/or one or more components of device100 as described in greater detail below, in consistent contact with theexterior body surface. Seal 112 may be attached to housing 104 by anysuitable means, including without limitation adhesion, fastening bystitching, stapling, or other penetrative means, snapping together orotherwise engaging interlocking parts, or the like. Seal 112 may beremovably attached to housing 104, where removable attachment signifiesattachment according to a process that permits repeated attachment anddetachment without noticeable damage to housing 104 and/or seal 112, andwithout noticeable impairment of an ability to reattach again by thesame process. As a non-limiting example, pliable seal 112 may be placedon an ear cup (for instance shown for exemplary purposes in FIG. 3) ofthe housing 104; pliable seal maybe formed of materials and/or in ashape suitable for use as an ear seal in an ear cup of a helmet, anover-ear headphone or hearing protection device, or the like. Personsskilled in the art, upon reviewing this disclosure in its entirety, willbe aware of forms and material properties suitable for use as seal 112,including without limitation a degree and/or standard of pliabilityrequired and/or useful to function as a seal 112 in this context.

With continued reference to FIGS. 1-5, housing 104 may include, beincorporated in, or be attached to an element containing additionalcomponents to device 100. For instance, in an embodiment, housing 104may include, be incorporated in, or be attached to a headset; headsetmay include, without limitation, an aviation headset, such as headsetsas manufactured by the David Clark company of Worcester Mass., orsimilar apparatuses. In some embodiments, housing 104 is headset; thatis, device 100 may be manufactured by incorporating one or morecomponents into the headset, using the headset as a housing 104. As afurther non-limiting example, housing 104 may include a mask; a mask asused herein may include any device or element of clothing that is wornon a face of user during operation, occluding at least a part of theface. Masks may include, without limitation, safety googles, gas masks,dust masks, self-contained breathing apparatuses (SCBA), self-containedunderwater breathing apparatuses (SCUBA), and/or other devices worn onand at least partially occluding the face for safety, functional, oraesthetic purposes. Housing 104 may be mask; that is, device 100 may bemanufactured by incorporating one or more elements or components ofdevice 100 in or on mask, using mask as housing 104. Housing 104 mayinclude, be incorporated in, or be attached to an element of headgear,defined as any element worn on and partially occluding a head or craniumof user. Headgear may wholly or partially occlude user's face and thusalso include a mask; headgear may include, for instance, a fullyenclosed diving helmet, space helmet or helmet incorporated in a spacesuit, or the like. Headgear may include a headband, such as withoutlimitation a headband of a headset, which may be an aviation headset.Headgear may include a hat. Headgear may include a helmet, including amotorcycle helmet, a helmet used in automobile racing, any helmet usedin any military process or operation, a construction “hardhat,” abicycle helmet, or the like. In an embodiment, housing 104 is shaped toconform to a particular portion of user anatomy when placed on exteriorbody surface; when placed to so conform, housing 104 may position atleast a sensor and/or user-signaling device 128 in a locus chosen asdescribed in further detail below. For instance, where housing 104 isincorporated in a helmet, mask, earcup or headset, housing 104 may bepositioned at a particular portion of user's head when helmet, mask,earcup or headset is worn, which may in turn position at least a sensorand/or user-signaling device 128 at a particular locus on user's head orneck.

Continuing to refer to FIGS. 1-5, device 100 includes at least aphysiological sensor 116. At least a physiological sensor 116 isconfigured to detect at least a physiological parameter and transmit anelectrical signal as a result of the detection; transmission of anelectrical signal, as used herein, includes any detectable alternationof an electrical parameter of an electrical circuit incorporating atleast a physiological sensor 116. For instance, at least a physiologicalsensor 116 may increase or reduce the impedance and/or resistance of acircuit to which at least a physiological sensor 116 is connected. Atleast a physiological sensor 116 may alter a voltage or current level,frequency, waveform, amplitude, or other characteristic at a locus incircuit. Transmission of an electrical signal may include modulation oralteration of power circulating in circuit; for instance transmissionmay include closing a circuit, transmitting a voltage pulse throughcircuit, or the like. Transmission may include driving a non-electricsignaling apparatus such as a device for transmitting a signal usingmagnetic or electric fields, electromagnetic radiation, optical orinfrared signals, or the like.

Still referring to FIGS. 1-5, at least a physiological parameter, asused herein, includes any datum that may be captured by a sensor, anddescribing a physiological state of user. At least a physiologicalparameter may include at least a circulatory and/or hematologicalparameter, which may include any detectable parameter describing thestate of blood vessels such as arteries, veins, or capillaries, anydatum describing the rate, volume, pressure, pulse rate, or other stateof flow of blood or other fluid through such blood vessels, chemicalstate of such blood or other fluid, or any other parameter relative tohealth or current physiological state of user as it pertains to thecardiovascular system. As a non-limiting example, at least a circulatoryparameter may include a blood oxygenation level of user's blood. Atleast a circulatory parameter may include a pulse rate. At least acirculatory parameter may include a blood pressure level. At least acirculatory parameter may include heart rate variability and rhythm. Atleast a circulatory parameter may include a plethysmograph describinguser blood-flow; in an embodiment, plethysmograph may describe areflectance of red or near-infrared light from blood. One circulatoryparameter may be used to determine, detect, or generate anothercirculatory parameter; for instance, a plethysmograph may be used todetermine pulse and/or blood oxygen level (for instance by detectingplethysmograph amplitude), pulse rate (for instance by detectingplethysmograph frequency), heart rate variability and rhythm (forinstance by tracking pulse rate and other factors over time), and bloodpressure, among other things. At least a physiological sensor may beconfigured to detect at least a hematological parameter of at least abranch of a carotid artery; at least a physiological parameter may bepositioned to capture the at least a hematological parameter byplacement on a location of housing that causes at least a physiologicalsensor to be placed in close proximity to the at least a branch; forinstance, where housing is configured to be mounted to a certainlocation on a user's cranium, and in a certain orientation, such as whenhousing forms all or part of a helmet, headset, mask, element ofheadgear, or the like, at least a physiological sensor may include asensor so positioned on the housing or an extension thereof that it willcontact or be proximate to a locus on the user's skin under which the atleast a branch runs. As a non-limiting example, where device 100 formsan earcup or earphone, at least a physiological sensor 116 may include asensor disposed on or embedded in a portion of the earcup and/orearphone contacting a user's skin over a major branch of the externalcarotid artery that runs near or past the user's ear.

In an embodiment, and still viewing FIGS. 1-5, detection ofhematological parameters of at least a branch of a carotid artery mayenable device 100 to determine hematological parameters of a user'scentral nervous system with greater accuracy than is typically found indevices configured to measure hematological parameters. For instance, ablood oxygen sensor placed on a finger or other extremity may detect lowblood oxygen levels in situations in which the central nervous system isstill receiving adequate oxygen, because a body's parasympatheticresponse to decreasing oxygen levels may include processes whereby bloodperfusion to the appendages is constricted in order to sustain higheroxygen levels to the brain; in contrast, by directly monitoring theoxygenation of a major branch of the external carotid artery, themeasurement of oxygenation to the central nervous system may be morelikely to achieve a more accurate indication of oxygen saturation than aperipheral monitor. Use of the carotid artery in this way may furtherresult in a more rapid detection of a genuine onset of hypoxemia; as aresult, a person such as a pilot that is using device 100 may be able tofunction longer under conditions tending to induce hypoxemia, knowingthat an accurate detection of symptoms may be performed rapidly andaccurately enough to warn the user. This advantage may both aid in andbe augmented by use with training processes as set forth in furtherdetail below.

With continued reference to FIGS. 1-5, at least a physiological sensor116 may include a hydration sensor; hydration sensor may determine adegree to which a user has an adequate amount of hydration, wherehydration is defined as the amount of water and/or concentration ofwater versus solutes such as electrolytes in water, in a person's body.Hydration sensor may use one or more elements of physiological data,such as sweat content and/or hematological parameters detected withoutlimitation using plethysmography, to determine a degree of hydration ofa user; degree of hydration may be associated with an ability to performunder various circumstances. For instance, a person with adequatehydration may be better able to resist the effects of hypoxemia inhigh-altitude and/or high-G for longer or under more severecircumstances, either because the person's body is better able torespond to causes of hypoxemia and delay onset, or because the person isbetter able to cope with diminished blood oxygen; this may be true ofother conditions and/or physiological states detected using at least aphysiological sensor 116, and may be detected using heuristics orrelationships derived, without limitation, using machine learning and/ordata analysis as set forth in further detail below.

Still referring to FIGS. 1-5, at least a physiological sensor 116 mayinclude a volatile organic compound (VOC) sensor. VOC sensor may senseVOCs, including ketones such as acetone; a user may emit ketones ingreater quantities when undergoing some forms of physiological stress,including without limitation hypoglycemia resulting from fasting oroverwork, which sometimes results in a metabolic condition known asketosis. As a result, detections of higher quantities of ketones mayindicate a high degree of exhaustion or low degree of available energy;this may be associated with a lessened ability to cope with otherphysiological conditions and/or parameters that may be detected by orusing at least a physiological sensor 116, such as hypoxemia, and/orenvironmental stressors such as high altitude or G-forces. Suchassociations may be detected or derived using data analysis and/ormachine learning as described in further detail below.

With continued reference to FIGS. 1-5, at least a physiologicalparameter may include neural oscillations generated by user neurons,including without limitation neural oscillations detected in the user'scranial region, sometimes referred to as “brainwaves.” Neuraloscillations include electrical or magnetic oscillations generated byneurological activity, generally of a plurality of neurons, includingsuperficial cranial neurons, thalamic pacemaker cells, or the like.Neural oscillations may include alpha waves or Berger's waves,characterized by frequencies on the order of 7.5-12.5 Hertz, beta waves,characterized by frequencies on the order of 13-30 Hertz, delta waves,having frequencies ranging from 1-4 Hertz, theta waves, havingfrequencies ranging from 4-8 Hertz, low gamma waves having frequenciesfrom 30-70 Hertz, and high gamma waves, which have frequencies from70-150 Hertz. Neurological oscillations may be associated with degreesof wakefulness, consciousness, or other neurological states of user, forinstance as described in further detail below. At least a sensor maydetect body temperature of at least a portion of user's body, using anysuitable method or component for temperature sensing.

Still referring to FIGS. 1-5, at least a physiological sensor 116 mayinclude an optical sensor, which detects light emitted, reflected, orpassing through human tissue. Optical sensor may include a near-infraredspectroscopy sensor (NIRS). A NIRS, as used herein, is a sensor thatdetects signals in the near-infrared electromagnetic spectrum region,having wavelengths between 780 nanometers and 2,500 nanometers. FIG. 6illustrates an exemplary embodiment of a NIRS 600 against an exteriorbody surface, which may include skin. NIRS 600 may include a lightsource 604, which may include one or more light-emitting diodes (LEDs)or similar element. Light source 604 may, as a non-limiting example,convert electric energy into near-infrared electromagnetic signals.Light source 604 may include one or more lasers. NIRS 600 may includeone or more detectors 608 configured to detect light in thenear-infrared spectrum. Although the wavelengths described herein areinfrared and near-infrared, light source 604 may alternatively oradditionally emit light in one or more other wavelengths, includingwithout limitation blue, green, ultraviolet, or other light, which maybe used to sense additional physiological parameters. In an embodiment,light source may include one or more multi-wavelength light emitters,such as one or more multi-wavelength LEDs, permitting detection ofblood-gas toxicology. Additional gases or other blood parameters sodetected may include, without limitation CO2 saturation levels, state ofhemoglobin as opposed to blood oxygen saturation generally. One or moredetectors 608 may include, without limitation, charge-coupled devices(CCDs) biased for photon detection, indium gallium arsenide (InGaAs)photodetectors, lead sulfide (PbS) photodetectors, or the like. NIRS 600may further include one or more intermediary optical elements (notshown), which may include dispersive elements such as prisms ordiffraction gratings, or the like. In an embodiment, NIRS 600 may beused to detect one or more circulatory parameters, which may include anydetectable parameter further comprises at least a circulatory parameter.At least a physiological sensor 116 may include at least two sensorsmounted on opposite sides of user's cranium.

Referring again to FIGS. 1-5, at least a physiological sensor 116 mayinclude a neural activity sensor. A neural activity sensor, as usedherein, includes any sensor disposed to detect electrical or magneticphenomena generated by neurons, including cranial neurons such as thoselocated in the brain or brainstem. Neural activity sensor may include anelectroencephalographic sensor. Neural activity sensor may include amagnetoencephalographic sensor. In an embodiment, neural activity sensormay be configured to detect neural oscillations. At least a sensor mayinclude an eye-tracking sensor, such as one or more cameras for trackingthe eyes of user. Eye-tracking sensor may include, as a non-limitingexample, one or more electromyographic (EMG) sensors, which may detectelectrical activity of eye muscles; electrical activity may indicateactivation of one or more eye muscles to move the eye and used by acircuit such as an alert circuit as described below to determine amovement of user's eyeball, and thus its current location of focus.

Continuing to refer to FIGS. 1-5, device 100 may communicate with one ormore physiological sensors that are not a part of device 100; one ormore physiological sensors may include any sensor suitable for use as atleast a physiological sensor 116 and/or any other physiological sensor.Communication with physiological sensors that are not part of device maybe accomplished by any means for wired or wireless communication betweendevices and/or components as described herein. Device may detect and/ormeasure at least a physiological parameter using any suitablecombination of at least a physiological sensor and/or physiologicalsensors that are not a part of device 100. Device 100 may combine two ormore physiological parameters to detect a physiological condition and/orphysiological alarm condition. For instance, and without limitation,where device 100 is configured to detect hypoxic incapacitation and/orone or more degrees of hypoxemia as described in further detail below,device 100 may perform such determination using a combination of heartrate and blood oxygen saturation, as detected by one or more sensor asdescribed above.

Still viewing FIGS. 1-5, at least a physiological sensor 116 may beattached to housing 104; attachment to housing 104 may include mountingon an exterior surface of housing 104, incorporation within housing 104,electrical connection to another element within housing 104, or thelike. Alternatively or additionally, at least a physiological sensor 116may include a sensor that is not attached to housing 104 or isindirectly attached via wiring or the like. As a non-limiting example,at least a physiological sensor 116 and/or one or more componentsthereof may be coupled to the pliable seal 112. In an embodiment, atleast a physiological sensor 116 may be contacting exterior bodysurface; this may include direct contact with the exterior body surface,or indirect contact for instance through a portion of seal 112 or othercomponents of device 100. In an embodiment, at least a physiologicalsensor 116 may contact a locus on the exterior body surface wheresubstantially no muscle is located between the exterior body surface andan underlying bone structure, meaning muscle is not located between theexterior body surface and an underlying bone structure and/or any muscletissue located there is unnoticeable to a user as a muscle and/orincapable of appreciably flexing or changing its width in response toneural signals; such a locus may include, as a non-limiting example,locations on the upper cranium, forehead, nose, behind the ear, at theend of an elbow, on a kneecap, at the coccyx, or the like. Location at alocus where muscle is not located between exterior body surface andunderlying bone structure may decrease reading interference and/orinaccuracies created by movement and flexing of muscular tissue. Atleast a physiological sensor 116 may contact a locus having little or nohair on top of skin. At least a physiological sensor 116 may contact alocus near to a blood vessel, such as a locus where a large artery suchas the carotid artery or a branch thereof, or a large vein such as thejugular vein, runs near to skin or bone at the location; in anembodiment, such a position may permit at least a physiological sensor116 to detect circulatory parameters as described above.

Referring now to FIG. 7, a schematic diagram of anatomy of a portion ofa user cranium 700 is illustrated for exemplary purposes. At least aphysiological sensor 116 may, for instance, be placed at or near to alocus adjacent to a branch 704 of a carotid artery, which may be abranch of an exterior carotid artery. At least a physiological sensor116 may be placed at a location 708 where substantially no muscle isfound between a user's skin and bone; such a location may be found, forinstance, near to the user's neck behind the ear. In an embodiment, atleast a physiological sensor may be placed in a locus that is bothadjacent to a branch 704 of a carotid artery and has substantially nomuscle between skin and bone. In an embodiment, measurement of at leasta physiological parameter, including without limitation pulseoxygenation and/or pulse rate as described in further detail below, on aparticular portion of the cranium may eliminate interfering factors suchas sweat and movement artifact; measurement above the neck may furthereliminate measurement issues experienced at the extremities (finger,wrist) due to temperature variation, movement and blood pooling under G.Where multiple physiological sensors of at least a physiological sensor116 are used, at least two sensors may be placed at two locations on auser's cranium; for instance, two sensors, one on each side of thecranium, may provide validation of consistent data, and assures a highcapture rate of data in flight. Two sensors may be so placed, as notedelsewhere in this disclosure, by form and/or configuration of housing104; for instance, housing 104 may include two earcups or other over-eardevices as described above.

As a non-limiting example of placement of at least a physiologicalsensor 116, and as illustrated for exemplary purposes in FIGS. 1-5, atleast a physiological sensor 116 may include a sensor mounted on an edgeof an earcup, and so positioned that placement of earcup over user's earplaces sensor in contact with user's head just behind the ear at a localskeletal eminence, with substantially no muscle tissue between skin andbone and a branch of the carotid artery nearby for detection ofcirculatory parameters. Similarly, where housing 104 includes a mask asdescribed above, a sensor of at least a physiological sensor 116 may bedisposed within mask at a location that, when mask is worn, placessensor against a forehead of user.

Still viewing FIGS. 1-5, where at least a physiological sensor 116includes a neural activity sensor, at least a physiological sensor 116may include one or more sensors placed in locations suitable fordetection of neural activity, such as on upper surfaces of a cranium ofuser, or similar locations as suitable for EEG or MEG detection andmeasurement.

With continued reference to FIGS. 1-5, device 100 includes a trainingand feedback processor 120 in communication with the at least aphysiological sensor. As used herein, a device, component, or circuit is“in communication” where the device, component, or circuit is able toreceive data from and/or transmit data to another device, component, orcircuit. In an embodiment, devices are placed in communication byelectrically coupling at least an output of one device, component, orcircuit to at least an input of another device, component, or circuit.Devices may further be placed in communication by creating an optical,inductive, or other coupling between two or more devices. Devices incommunication may be placed in near field communication with oneanother. Two or more devices may be in communication where the two ormore devices are configured to send and/or receive signals to or fromeach other. Placement of devices in communication may include direct orindirect connection and/or transmission of data; for instance, two ormore devices may be connected or otherwise in communication by way of anintermediate circuit. Placement of devices in communication with eachother may be performed via a bus or other facility forintercommunication between elements of a computing device as describedin further detail below in reference to FIG. 11. Placement of devices incommunication with each other may include fabrication together on ashared integrated circuit and/or wafer; for instance, and withoutlimitation, two or more communicatively coupled devices may be combinedin a single monolithic unit or module.

With continued reference to FIGS. 1-5, training and feedback processor120 may be constructed according to any suitable process or combinationof processes for constructing an electrical circuit; for instance, andwithout limitation, training and feedback processor 120 may include aprinted circuit board. Training and feedback processor 120 may include abattery or other power supply; where training and feedback processor 120is integrated in one or more other systems as described in furtherdetail below, training and feedback processor 120 may draw electricalpower from one or more circuit elements and/or power supplies of suchsystems. Training and feedback processor 120 may include a memory;memory may include any memory as described below in reference to FIG.11. Training and feedback processor 120 may include one or moreprocessors as described in further detail below in reference to FIG. 11,including without limitation a microcontroller or low-powermicroprocessor. In an embodiment, memory may be used to store one ormore signals received from at least a physiological sensor 116.

Still referring to FIGS. 1-5, training and feedback processor 120 may bein communication with at least an environmental sensor 124; at least anenvironmental sensor 124 may be any sensor configured to detect at leastan environmental parameter, defined herein as a parameter describingnon-physiological data concerning user or surroundings of user, such asacceleration, carbon monoxide, or the like. At least an environmentalsensor 124 may include at least a motion sensor, including withoutlimitation one or more accelerometers, gyroscopes, magnetometers, or thelike; at least a motion sensor may include an inertial measurement unit(IMU). At least an environmental sensor 124 may include at least atemperature sensor. At least an environmental sensor 124 may include atleast an air quality sensor, such as without limitation a carbonmonoxide sensor, or other sensor of any gas or particulate matter inair. At least an environmental sensor may include an atmospheric oxygensensor, an oxygen flow meter, and/or a mask oxygen/CO₂ sensor. At leastan environmental sensor 124 may include at least a barometric sensor. Atleast an environmental sensor 124 may include a pressure sensor, forinstance to detect air or water pressure external to user. Training andfeedback processor 120 may be attached to housing 104, for instance byincorporation within housing 104; as a non-limiting example and as shownin FIG. 5, the training and feedback processor 120 may be housed alongan inner wall of the housing 104. Training and feedback processor 120may be attached to an exterior of housing 104. According to anembodiment, a covering may be placed over housing 104, fully enclosingthe training and feedback processor 120 within the housing 104; theenclosure may include a plastic, a metal, a mesh-type material, and/orany other suitable material. Training and feedback processor 120 may bein another location not attached to or incorporated in housing 104.Training and feedback processor 120 may be incorporated into and/orconnected to one or more additional elements including any elementsincorporating or connected to user signaling devices as described infurther detail below. As an alternative to storage of one or moreparameter values such as physiological parameters or environmentalparameters in memory, alert circuit may transmit the data to one or moreremote storage mediums through one or more wired and/or wireless means.

Still viewing FIGS. 1-5, training and feedback processor 120 may beconfigured to receive at least a signal from the at least aphysiological sensor 116, generate an alarm as a function of the atleast a signal, and to transmit the alarm to a user-signaling device 128in communication with the training and feedback processor 120. Trainingand feedback processor 120 may periodically sample data from at least asensor; in a non-limiting example, data may be sampled 75 times persecond. In an embodiment, alarm is generated upon detection of anysignal at all from at least a physiological sensor 116; for instance, atleast a physiological sensor 116 may be configured only to signaltraining and feedback processor 120 upon detection of a problematic orotherwise crucial situation. Alternatively or additionally, training andfeedback processor 120 is further configured to detect a physiologicalalarm condition and generate the alarm as a function of thephysiological alarm condition. In an embodiment, a physiological alarmcondition includes any physiological condition of user that may endangeruser or impair user's ability to perform an important task; as anon-limiting example, if user is flying an aircraft and user'sphysiological condition is such that user is unable to concentrate,respond rapidly to changing conditions, see or otherwise sense flightcontrols or conditions, or otherwise successfully operate the aircraftwithin some desired tolerance of ideal operation, a physiological alarmcondition may exist, owing to the possibility of inefficient ordangerous flight that may result. Similarly, if user's physiologicalcondition indicates user is experiencing or about to experience physicalharm, is losing or is about to lose consciousness, or the like, aphysiological alarm condition may exist.

Still referring to FIGS. 1-5, training and feedback processor 120 may beconfigured to perform any embodiment of any method and/or method step asdescribed in this disclosure. For instance, and without limitation,training and feedback processor 120 may be designed and configured todetect at least a flight condition having a causative association withhypoxemia, measure, using at least a physiological sensor, at least aphysiological parameter associated with hypoxemia, and determine, by thetraining and feedback processor 120, and based on the at least aphysiological parameter, a degree of pilot hypoxemia.

In an embodiment, and still viewing FIGS. 1-5, detection of aphysiological alarm condition may include comparison of at least aphysiological parameter to a threshold level. For instance, and withoutlimitation, detection of the physiological alarm condition furthercomprises determination that the at least a physiological parameter isfalling below a threshold level; as an example, blood oxygen levelsbelow a certain cutoff indicate an imminent loss of consciousness, asmay blood pressure below a certain threshold. Similarly detection of aphysiological alarm condition may include detection of alpha waveactivity falling below a certain point, which may indicate entry intoearly stages of sleep or a hypnogogic state, and/or entry intounconsciousness. Comparison to threshold to detect physiological alarmcondition may include comparison of at least a physical parameter to avalue stored in memory, which may be a digitally stored value;alternatively or additionally comparison may be performed by analogcircuitry, for instance by comparing a voltage level representing atleast a physical parameter to a reference voltage representing thethreshold, by means of a comparator or the like. Threshold may representor be represented by a baseline value. Detection of a physiologicalalarm condition may include comparison to two thresholds; for instance,detection that incapacitation and/or loss of consciousness due tohypoxemia is imminent may include detection that a user's heart rate hasexceeded one threshold for heart rate and simultaneous or temporallyproximal detection that blood oxygen saturation has fallen below asecond threshold. Threshold or thresholds used for such comparison todetect a physiological alarm condition may include universal and/ordefault thresholds. For instance, device 100 may be set, prior to usewith a particular individual, with thresholds corresponding to a typicaluser's response to physiological conditions. For instance, device 100may initially store a threshold in memory of device 100 of 70% bloodoxygen saturation, as indicating that a typical user is likelyincapacitated by hypoxemia when blood oxygen saturation of that user,including blood oxygen saturation in a cranial vessel such as a branchof a carotid artery, has fallen below 70%; however, data gatheredregarding a particular user may indicate that the particular user isonly likely to be incapacitated at 65% blood oxygen saturation and/orthat the particular user is likely to be incapacitated at 75% bloodoxygen saturation, and threshold may be modified in memory accordingly.

Still referring to FIGS. 1-5, in an embodiment, a single physiologicalparameter and/or combination of physiological parameters may beassociated with a plurality of thresholds indicating a plurality ofdegrees of physiological conditions, such as degrees of incapacitation.As a non-limiting example, a plurality of thresholds may be storedregarding blood oxygen saturation, such as without limitation a firstthreshold indicating a possible saturation problem, a second indicatinga degree of blood oxygen saturation consistent with some degree ofperformance degradation on the part of the user, and a third thresholdindicating that incapacitation is likely. By way of illustration, andwithout limitation, default or factory-set thresholds may include afirst threshold triggered upon a user crossing into 80-90% blood oxygensaturation, indicating “saturation possible problem,” a second thresholdupon the user crossing into 70-80% saturation, indicating “Performancedegraded,” and a third threshold upon the user crossing into <70%saturation indicating “incapacitation likely,” while 90-100% saturationmay indicate a normal amount of blood oxygen saturation. Generally,multiple thresholds may be set just above physiologically-relevantlevels corresponding to onset of symptoms, cognitive impairment, andtotal incapacitation for a very-accurate, user-specific warning tone.User-specific thresholds at any tier or degree of incapacitation may beset and/or adjusted according to an iterative process, where usersdefine thresholds, and/or the system finds user thresholds based on, asa non-limiting example, user-specific training and/or sortie data.Determination that of an alarm state such as alarm states associatedwith one or more thresholds as described above may alternatively oradditionally be performed without a threshold comparison, for instanceby identifying a correlation of two or more sensor data determined, forinstance using machine learning as described below, to be associatedwith entry into such one or more alarm states; as a non-limitingexample, detection of imminent incapacitation and/or unconsciousness dueto hypoxemia may be accomplished by detecting a simultaneous ortemporally correlated increase in heart rate and decrease in bloodoxygen saturation. Combinations or associations of sensor data mayfurther involve measuring several human performance metrics includingSPO2, Pulse Rate, and full plethysmograph as well as environmentalsensor data such as flight conditions for full characterization andcorrelation of human performance in flight, for instance as described infurther detail below.

Still referring to FIGS. 1-5, detection of physiological alarm conditionmay include comparing at least a physiological parameter to at least abaseline value and detecting the physiological alarm condition as afunction of the comparison. At least a baseline value may include anumber or set of numbers representing normal or optimal function ofuser, a number or set of numbers representing abnormal or suboptimalfunction of user, and/or a number or set of numbers indicating one ormore physiological parameters demonstrating a physiological alarmcondition. At least a baseline value may include at least a threshold asdescribed above. In an embodiment, at least a baseline value may includea typical user value for one or more physiological parameters. Forexample, and without limitation, at least a baseline value may include ablood oxygen level, blood pressure level, pulse rate, or othercirculatory parameter, or range thereof, consistent with normal or alertfunction in a typical user; at least a baseline value may alternativelyor additionally include one or more such values or ranges consistentwith loss of consciousness or impending loss of consciousness in atypical user. Similarly, at least a baseline value may include a rangeof neural oscillations typically associated in users with wakeful oralert states of consciousness, and/or a range of neural oscillationstypically associated with sleeping or near-sleeping states, loss ofconsciousness or the like. Training and feedback processor 120 mayreceive a typical user value and using the typical user value as thebaseline value; for instance, training and feedback processor 120 mayhave typical user value entered into memory of training and feedbackprocessor 120 by a user or may receive typical user value over a networkor from another device. At least a baseline value may be maintained inany suitable data structure, including a table, database, linked list,hash table, or the like.

Continuing to refer to FIGS. 1-5, typical user value may include a uservalue matched to one or more demographic facts about user. For instance,a pulse rate associated with loss of consciousness in women may not beassociated with loss of consciousness in men, or vice-versa; where useris a woman, the former pulse rate may be used as a baseline value forpulse rate. Baseline value may similarly be selected using a typicalvalue for persons matching user's age, sex, height, weight, degree ofphysical fitness, physical test scores, ethnicity, diet, or any othersuitable parameter. Typical user baseline value may be generated byaveraging or otherwise aggregating baseline values calculated per useras described below; for instance, where each user has baseline valuesestablished by collection of physiological parameters using devices suchas device 100, such values may be collected, sorted according to one ormore demographic facts, and aggregated to produce a typical userbaseline value to apply to user. Still referring to FIGS. 1-5, baselinevalue may be created by collection and analysis of at least aphysiological parameter; collection and/or analysis may be performed bytraining and feedback processor 120 and/or another device incommunication with training and feedback processor 120. For instance,receiving a baseline value may include collecting a plurality of samplesof the at least a physiological parameter and calculating the baselinevalue as a function of the plurality of samples. Device 100 maycontinuously or periodically read or sample signals from at least aphysiological sensor 116, recording the results; such results may betimestamped or otherwise co-associated, such that patterns concerningphysiological parameters may be preserved, detected, and/or analyzed.For example and without limitation, user pulse rate and/or bloodpressure may vary in a consistent manner with blood oxygen level; userblood pressure and/or pulse rate may further vary in a consistent mannerwith brain wave activity. Additional information from other sensors maysimilarly collected to form baseline value; for instance, where user isoperating a machine, such as an aircraft, data concerning operation,such as flight control data, may be collected and associated with atleast a physiological parameter. As a non-limiting example, user'sreaction time when operating an aircraft may be measurably slower whenuser's blood pressure is below a certain amount, while showing noparticular change for variations in blood pressure above that amount.Additional information may further be provided by user and/or anotherperson evaluation user behavior and/or performance. For example, duringtest flights or other operation of an aircraft where user and/oraircraft may be observed, user, a supervisor, or another observer mayrecord information such as the user's performance, the user's feelingsor apparent state of health, the performance of the aircraft, and thelike. Some factors that may be relatively objectively monitoredregarding the overall state of health experience by the user may includehow many times the user has to use “anti-G” breathing exercises, orsimilar activities. In an embodiment, data is received from user and/orobservers via numerical ratings, or selections of buttons or other entrydevices that map to numerical ratings. Alternatively or additionally,entries may be formed using one or more text entries; text entries maybe mapped to numerical ratings or the like using, as a non-limitingexample, natural language analysis, textual vector analysis, or thelike. Plurality of physiological parameters and/or user entries andother entries may be collected over time, during, for instance a seriesof routine activities by user.

Continuing to refer to FIGS. 1-5, baseline value may be generated bycollection of data from at least an environmental sensor 124. Forinstance, each set of one or more physiological parameters taken at aparticular moment, or over a particular period of time, may be linked inmemory to one or more environmental parameters, including withoutlimitation motion-sensor data, air quality data, and the like. This maybe used by device 100, as a non-limiting example, to collectrelationships between environmental parameters and physiologicalparameters, such as a relationship between localized or systemic bloodpressure, G-forces, and state of consciousness of a user in an aircraft,or a relationship between quality of neural oscillations and externalwater pressure in a diver. This in turn may be used to produceadditional baseline information as described in further detail below. Asfurther examples, relationships determined to achieve baseline valuesmay include comparisons of heart rate, heart rate increase and heartrate recovery are easily compared to scientifically derived normsestablished in academia and professional athletics. Relationships mayinclude correlation of blood oxygen saturation, heart rate and heartrate variability. These metrics may be useful for objectivelydetermining deliberate risk levels associated with human performance,for instance using population data and/or machine learning as describedin further detail below. In an embodiment, a baseline study of eachindividual performance against known conditions, such as in theRestricted Oxygen Breathing Device, may be performed prior to use ofdevice 10; a purpose of the baseline evaluation may be to assess howeach individual responds to specific conditions. Such a response may beused to both validate the data to draw usable conclusions, as well as tocalibrate the alarm system to provide meaningful data while reducing theincidence of false alarms, for instance by setting and/or adjustingdefault threshold levels as described above.

With continued reference to FIGS. 1-5, plurality of physiologicalparameters, plurality of environmental parameters, and/or user-entereddata may be aggregated, either independently or jointly. For instance,device 100 may calculate an average level, for one or more parameters ofat least a physiological parameter, associated with normal or optimalfunction, health, or performance of user; a standard deviation from theaverage may also be calculated. This may be used, e.g., to generate analarm indicating that, for instance, a given physiological parameter hasrecently shifted more than a threshold amount from its average value.Threshold amount may be determined based on amounts by which a typicaluser may deviate from average amount before experiencing discomfort,loss of function, or loss of consciousness. Threshold amount may be setas some multiple of standard deviations, as calculated from sensedphysiological parameters; for instance, two or more standard deviationsfrom an average value for a given detected physiological parameter maytrigger an alarm.

Alternatively or additionally, and still referring to FIGS. 1-5,aggregation may include aggregation of relationships between two or moreparameters. For instance, and without limitation, aggregation maycalculate a relationship between a first physiological parameter of theat least a physiological parameter and a second physiological parameterof the at least a physiological parameter; this relationship may becalculated, as a non-limiting example, by selecting a first parameter asa parameter associated with a desired state for the user and a secondparameter known or suspected to have an effect on the first parameter.For example, first parameter may be blood oxygen level, and secondparameter may be blood pressure, such as localized blood pressure in acranial region; a reduction in cranial blood pressure may be determinedto be related to a reduction in cranial blood oxygen level, which inturn may be related to loss of consciousness or other loss of functionin user or in a typical user. As another example, aggregation maycalculate a relationship between a physiological parameter of the atleast a physiological parameter and an environmental parameter. Forexample, blood oxygen level may be inversely related to an amount ofacceleration or G force a user is experiencing in an aircraft; thisrelationship may be directly calculated from those two values, orindirectly calculated by associating the amount of acceleration or Gforce with a degree of decrease in cranial blood pressure, which maythen be related to blood oxygen levels. Aggregation may calculate arelationship between at least a physiological parameter and user-entereddata; for instance, people observing user may note losses of performanceor apparent function at times associated with a certain degree ofdecrease in blood oxygen level or some other physiological parameter.The relationships may be between combinations of parameters: forinstance, loss of function may be associated with an increase in Gforces coupled with a decrease in pulse rate, or a decrease in bloodoxygen coupled with a decrease in alpha waves, or the like.

Still referring to FIGS. 1-5, relationships between two or more of anyof physiological parameters, environmental parameters, and/oruser-entered parameters may be determined by one or moremachine-learning algorithms. Machine-learning algorithms as used hereinare processes executed by computing devices to improve accuracy andefficiency of other processes performed by the computing devices, ordetect relationships between data sets, through statistical ormathematical measures of accuracy and efficiency. Machine learning mayfunction by measuring a difference between predicted answers or outputsand goal answers or outputs representing ideal or “real-world” outcomesthe other processes are intended to approximate. Predicted answers oroutputs may be produced by an initial or intermediate version of theprocess to be generated, which process may be modified as a result ofthe difference between predicted answers or outputs and goal answers oroutputs. Initial processes to be improved may be created by a programmeror user or may be generated according to a given machine-learningalgorithm using data initially available. Inputs and goal outputs may beprovided in two data sets from which the machine learning algorithm mayderive the above-described calculations; for instance a first set ofinputs and corresponding goal outputs may be provided and used to createa mathematical relationship between inputs and outputs that forms abasis of an initial or intermediate process, and which may be testedagainst further provided inputs and goal outputs. Data sets representinginputs and corresponding goal outputs may be continuously updated withadditional data; machine-learning process may continue to learn fromadditional data produced when machine learning process analyzes outputsof “live” processes produced by machine-learning processes. As anon-limiting example, an unsupervised machine-learning algorithm may beperformed on training sets describing co-occurrences of any or allparameters in time; unsupervised machine-learning algorithm maycalculate relationships between parameters and such co-occurrences. Thismay produce an ability to predict a likely change in a physiologicalparameter as a function of detected changes in one or more environmentalparameters; thus, a physiological alarm condition may be detected when aset of alarm parameters are trending in a way associated with decreasesin blood oxygen, causing a blood oxygen warning to be generated beforeany decrease in blood oxygen is detected. With continued reference toFIGS. 1-5, a supervised machine learning algorithm may be used todetermine an association between one or more detected parameters and oneor more physiological alarm conditions or other outcomes or situationsof interest or concern. For instance, a supervised machine-learningalgorithm may be used to determine a relationship between one or moresets of parameters, such as physiological parameters, environmentalparameters, and/or user-entered information, and one or morephysiological alarm conditions. To illustrate, a mathematicalrelationship between a set of physiological and environmental parametersas described above and a loss of consciousness, or near loss ofconsciousness, by user, may be detected by a supervised machine-learningprocess; such a process may include a linear regression process, forinstance, where a linear combination of parameters may is assumed to beassociated with a physiological alarm condition, and collected parameterdata and associated data describing the physiological alarm conditionare evaluated to determine the linear combination by minimizing an errorfunction relating outcomes of the linear combination and the real-worlddata. Polynomial regression may alternatively assume one or morepolynomial functions of parameters and perform a similar minimizationprocess. Alternatively or additionally neural net-based algorithms orthe like may be used to determine the relationship.

Still viewing FIGS. 1-5, each of the above processes for aggregationand/or machine learning may further be compared to test data, such asdata gathered concerning user physiological parameters, performance,and/or function, in one or more testing facilities or protocols; suchfacilities or protocols may include, for instance, centrifuge testing ofa user's response to acceleration and/or G forces, tests administered tomonitor one or more physiological parameters and/or user function orperformance under various adverse conditions such as sleep deprivation,boredom, and the like, or any other tests administered to determine theeffect of various conditions on user. Such test data may be collectedusing device 100, or alternatively may be collected using one or moreother devices, medical facilities, and the like. Any aggregation and/ormachine learning as described above may be applied to test data,independently or combined with other data gathered as described above;for instance, in an embodiment, test data may be combined with typicaluser data to achieve a first baseline, which may be compared to furtherdata gathered as described above to modify the baseline and generate asecond baseline using any suitable aggregation or machine-learningmethodology. Collected and/or aggregated data may be provided to users,such as supervisors or commanders, who may use collected and/oraggregated data to monitor state of health of individual users or groupsof users. In an embodiment, device 100 may store data collected during aperiod of activity, such as a flight where device 100 is used with apilot and may provide such data to another device upon completion of theperiod of activity. For instance, device 100 may download stored datainto a file for storage and tracking; data file may be analyzed using anindigenously designed application to determine areas of further study,allowing a detailed look at portions of ground operations or flight inwhich physio-logical responses can be compared to known conditions. Fileand/or collected data may be transferred to a remote computing devicevia network, wired, or wireless communication; for instance, and withoutlimitation, device 100 may be connected to or placed in communicationwith remote device after each flight or other period of activity. Wheredevice 100 is incorporated in an element of headgear such as a helmet,headset, and/or mask, such element of headgear may be connected viawired, wireless, and/or network connection to remote device.

With continued reference to FIGS. 1-5, in an illustrative example,detection of a physiological alarm condition may include determination,by the training and feedback processor 120, that the user is losingconsciousness. Alternatively or additionally, detection may includedetermination that user is about to lose consciousness. This may beachieved by comparing one or more physiological parameters and/orenvironmental parameters to a relationship, threshold, or baseline,which may be any relationship, threshold, or baseline as describedabove; for instance and without limitation, where blood oxygen leveldrops below a threshold percentage of a baseline level, below anabsolute threshold amount, below a certain number of standarddeviations, or the like, training and feedback processor 120 maydetermine that user is about to lose consciousness or is losingconsciousness, and issue an alarm. Alternatively or additionally,aggregation as described above may determine that imminent loss ofconsciousness is predicted by a particular set of values for one or moreparameters as described above, training and feedback processor 120 maydetect a physiological alarm condition by detecting the particular setof values, indicating that user is about to lose consciousness. In anembodiment, determination of user state and/or physiological alarmcondition may filter out anomalous or transient readings, or readingsaltered by motion of one or more elements of user's body or environment;for instance, determination may include determination of a particularparameter value for longer than a predetermined amount of time.

As another example, and still viewing FIGS. 1-5, detection of thephysiological alarm condition further comprises determination that theuser is falling asleep; this may occur, for instance, where a neuralactivity sensor detects that a user is entering into an early stage ofsleep, or “dozing off,” for instance by detection of a change inbrainwaves. In an embodiment, training and feedback processor 120 maygenerate an alarm where alpha wave activity drops by a thresholdpercentage, by a threshold amount, or the like; alternatively oradditionally, one or more sets of brainwave patterns determined bytraining and feedback processor 120 to be associated with user fallingasleep, for instance by aggregation or machine-learning methods asdescribed above, may be detected by training and feedback processor 120via at least a neural activity sensor, triggering an alarm. This may, asa non-limiting example, aid in preventing a commercial pilot who is notactively operating flight controls from partially or wholly fallingasleep, which is a particular concern on long flights.

With continued reference to FIGS. 1-5, detection of a physiologicalalarm condition may further include detection of at least anenvironmental parameter, and detection of physiological alarm conditionas a function of the at least an environmental parameter. For instance,aggregation and/or machine learning processes as described above maydetermine that a reduction in cranial blood pressure coupled with anincrease in acceleration indicates a probable loss of consciousness in auser; an alarm may therefore be triggered by detection, by training andfeedback processor 120, of that combination of decreased cranial bloodpressure and increased acceleration.

Still viewing FIGS. 1-5, training and feedback processor 120 mayincorporate or be in communication with at least a user-signaling device128. In an embodiment, at least a user-signaling device 128 may beincorporated in device 100; for instance, at least a user-signalingdevice 128 may be attached to or incorporated in housing 104. Where atleast a user-signaling device 128 contacts an exterior body surface ofuser, housing 104 may act to place at least a user-signaling device 128in contact exterior body surface of user. Alternatively or additionally,device 100 may communicate with a user-signaling device 128 that is notincorporated in device 100, such as a display, headset, or other deviceprovided by a third party or the like, which may be in communicationwith training and feedback processor 120. User-signaling device 128 maybe or incorporate a device for communication with an additionaluser-signaling device such as a vehicle display and/or helmet avionics;for instance, user-signaling device 128 may include a wirelesstransmitter or transponder in communication with such additionaldevices. In an embodiment, and without limitation, user-signaling device128 may be configured to indicate the degree of pilot hypoxemia to atleast a user, as described in further detail below.

Continuing to refer to FIGS. 1-5, at least a user-signaling device 128may include any device capable of transmitting an audible, tactile orvisual signal to a user when triggered to do so by training and feedbackprocessor 120. In an embodiment, and as a non-limiting example, at leasta user-signaling device 128 may include a bone-conducting transducer invibrational contact with a bone beneath the exterior body surface. Abone-conducting transducer, as used herein, is a device or componentthat converts an electric signal to a vibrational signal that travelsthrough bone placed in contact with the device or component to an innerear of user, which interprets the vibration as an audible signal.Bone-conducting transducer may include, for instance, a piezoelectricelement, which may be similar to the piezoelectric element found inspeakers or headphones, which converts an electric signal intovibrations. In an embodiment, bone-conducting transducer may be mountedto housing 104 in a position placing it in contact with a user's bone;for instance, where housing 104 includes or is incorporated in an earcup, housing 104 may place bone-conducting transducer in contact withuser's skull just behind the ear, over the sternocleidomastoid muscle.Likewise, where housing 104 includes a headset, mask, or helmet, housing104 may place bone-conducting transducer in contact with a portion ofuser's skull that is adjacent to or covered by headset, mask, or helmet.

Still referring to FIGS. 1-5, at least a user-signaling device 128 mayfurther include an audio output device. Audio output device may includeany device that converts an electrical signal into an audible signal,including without limitation speakers, headsets, headphones, or thelike. As a non-limiting example, audio output device may include aheadset speaker of a headset incorporating or connected to device 100, aspeaker in a vehicle user is traveling in, or the like. At least auser-signaling device 128 may include a light output device, which maybe any device that converts an electrical signal into visible light;light output device may include one or more light source 604s such asLEDs, as well as a display, which may be any display as described belowin reference to FIG. 11. At least a user-signaling device 128 mayinclude a vehicular display; at least a vehicular display may be anydisplay or combination of displays presenting information to a user of avehicle user is operating. For instance, at least a vehicular displaymay include any combination of audio output devices, light outputdevices, display screens, and the like in an aircraft flight console, acar dashboard, a boat dashboard or console, or the like; training andfeedback processor 120 may be in communication with vehicular displayusing any form of communicative coupling described above, includingwithout limitation wired or wireless connection. At least auser-signaling device 128 may include a helmet display; helmet displaymay include any visual, audio, or tactile display incorporated in anykind of helmet or headgear, which may be in communication with trainingand feedback processor 120 according to any form of communicativecoupling as described above.

Still viewing FIGS. 1-5, user-signaling device 128 and/or training andfeedback processor 120 may be programmed to produce a variety ofindications, which may correspond to various physiological alarmconditions and/or contexts. Possible indications may be, but are notlimited to: imminent unconsciousness, substandard oxygenation, erraticpulse, optimum oxygenation, and/or any other suitable indication, whilemaintaining the spirit of the present invention. Each such indicationmay have a distinct pattern of audible, visual, and/or textualindications; each indication may include, for instance, an audible ortextual warning or description of a physiological alarm condition. Anyof the above user-signaling devices 128 and/or signals may be usedsingly or in combination; for instance, a signal to user may include anaudio signal produced using a bone-conducting transducer, a verbalwarning message output by an audio output device, and a visual displayof an image or text indicating the physiological alarm condition.Persons skilled in the art, upon reviewing the entirety of thisdisclosure, will be aware of various combinations of signaling meansand/or processes that may be employed to convey a signal to user. In anembodiment, in addition to transmitting an alarm to user-signalingdevice 128, alert circuit may transmit a signal to one or more automatedvehicular controls or other systems to alleviate one or moreenvironmental parameters contributing to physiological alarm condition.For instance, and without limitation, an automated aircraft control mayreceive an indication of hypoxia while a motion sensor indicates highacceleration; aircraft control may reduce acceleration to alleviate thehypoxia. Persons skilled in the art, upon reviewing the entirety of thisdisclosure, may be aware of various additional ways in which automatedsystems may act to alleviate a physiological alarm condition asdescribed herein.

Referring now to FIG. 8, an exemplary embodiment of a method 800 ofmeasuring physiological parameters 100 is illustratively depicted. Atstep 805, a physiological parameter measuring device comprising ahousing 104, at least a physiological sensor 116, and a training andfeedback processor 120 in communication with the at least aphysiological sensor 116 is positioned on a user. This may be performed,for instance, as described above in reference to FIGS. 1-5. Positioningmay include mounting housing 104 on an exterior body surface of theuser. Positioning may include placing at least a physiological sensor116 in contact with exterior body surface. As a non-limiting example, atleast a physiological sensor 116 may rest behind the ear on the neck ofthe user, over the sternocleidomastoid muscle. In an embodiment,mounting device 100 to user includes mount a plurality of devices touser. For instance, and without limitation, where device 100 includes anear cup as described above, user may be outfitted with two such devices(one in each ear cup); low-confidence data points may be validated bythe second sensor, essentially “filling-in” the holes in data coverage.

At step 810, with continued reference to FIG. 8, training and feedbackprocessor 120 measures at least a physiological parameter using at leasta physiological sensor 116. In an embodiment, this may be performed asdescribed above in reference to FIGS. 1-5. For instance, where sensorincludes at least a NIRS 600 sensor, sensor may measure one or moresignals from the user pertaining to the oxygenation of the user. Thesignals may include, but are not limited to, pulse oximetry, pulse,temperature, and/or any other relevant measurement. NIRS 600 sensor mayemit near-infrared (red) light into soft tissue and measure how much ofthe near-infrared light is absorbed by said tissue and how much isreflected. According to an embodiment, the sensing components of theNIRS 600 sensor may act essentially as specialized photoresistors. Theirresistivity may change as a function of the intensity of light reflectedfrom the tissue. Since well-oxygenated blood (defined as oxygen-boundhemoglobin) absorbs more red light than poorly oxygenated blood, acorrelation between the resistivity of the sensor and the bloodoxygenation may be ascertained as a function of the resistivity.

Still viewing FIG. 8, at step 815, a physiological alarm condition isdetected by training and feedback processor 120 as a function of the atleast a physiological parameter. This may be implemented, for instance,as described above in reference to FIGS. 1-5. For example, and withoutlimitation, training and feedback processor 120 may predict whether auser is going to experience an impending lack of consciousness.According to an embodiment, training and feedback processor 120 mayconstantly monitor blood oxygenation by virtue of aNIRS sensor.According to an embodiment, when oxygenation drops by a predefinedpercentage, the training and feedback processor 120 may predict that theuser is going to experience an impending lack of consciousness. Anyother combination of physiological and/or environmental parameters maybe used to detect physiological alarm condition, as described above inreference to FIGS. 1-5.

With continued reference to FIG. 8, at step 820, training and feedbackprocessor 120 generates at least an alarm as a function of the detectedphysiological alarm condition. This may be performed as described abovein reference to FIGS. 1-5. Training and feedback processor 120 maysignal user as a function of detected physiological alarm condition;this may be implemented as described above in reference to FIGS. 1-5.For instance, and without limitation, where training and feedbackprocessor 120 predicts that the user is going to experience an impendinglack of consciousness, the training and feedback processor 120 may sendsa signal to bone conduction transducer, generating a user signal.Similarly, and as described above, training and feedback processor 120may further send a signal to a third-party device, either wirelessly orthrough a wired connection, alerting a third party of any relevantpredictions made by the training and feedback processor 120 while thedevice for measuring physiological parameters 100 is being used.

Device for measuring physiological parameters 100 may be used is variousfields, according to various embodiments of the present invention.According to an embodiment, the device for measuring physiologicalparameters 100 may be used in conjunction with military aviation. Forexample, the human performance oxygen sensor may be used for militaryaviation uses that rely on stored oxygen, e.g., for use in fighter jetsand high-altitude parachuting. During operation of fighter jets andwhile performing high altitude parachuting, there is a risk of hypoxiaand the inherent need to wear a helmet. The device for measuringphysiological parameters 100 may be incorporated into such helmets, thusmeasuring the wearer's vital oxygenation signals while the wearer iswearing the helmet.

According to various embodiments, device for measuring physiologicalparameters 100 may be used in conjunction with commercial aviationheadsets, firefighting uses, and/or in any other suitable field wherethe measurement of human oxygenation is relevant or necessary for thesafety of individuals or for any other relevant reason. According tovarious embodiments, iterative additional developments of the productinclude incorporation of a carbon dioxide sensor, reduction insize/weight, removal of the battery to utilize host system availablepower from the aircraft or vehicle, and/or the inclusion or exclusion ofvarious other suitable components while maintaining the spirit of thepresent principles. In testing performed using a reduced oxygenbreathing device (ROBD) to simulate atmospheric conditions at variousaltitudes, in which device 100 was compared to a conventionalfinger-mounted oxygen sensor, it was found that embodiments of device100 were able to detect decreased blood oxygen levels up to 15 secondsearlier than previously available systems, resulting in a substantiallyimproved opportunity for users to correct conditions leading to hypoxia;this in turn allowed users to avert symptoms of hypoxia in some cases,and generally to reduce the length and severity of symptoms, both ofwhich are crucial for improving outcomes during flight. Alarms weretriggered by device 100 just as users were reporting initial sensationof symptoms. Subsequent testing on flight sorties confirmed high degreesof reliability in detection of physiological alarm conditions.

According to various embodiments, device 100 may further includeincorporation of a pulse oximetry sensor and a carbon dioxide sensor toincorporate the existing product into a fire helmet. The and signalingmay be transmitted to an existing or newly developed two-way radiosystem in order to allow a fire chief to receive real-time data on allthe members of his firefighting force. By transmitting and receivingthis data, the fire chief is able to receive real time location andperformance data of every single member of his time, optimizing theteam's performance.

Embodiments of the above-described devices and methods may provide asystem that produces real-time, accurate physiological data analysis. Inan embodiment, sensing hematological parameters from a branch of auser's carotid artery enables more rapid and accurate detection ofphysiological conditions, such as hypoxemia; this may permit a user tooperate under difficult conditions for longer, knowing that a timely andaccurate warning system is in place to indicate when conditions shouldbe modified. Machine learning and data analysis may continuously improveformulas for detection of physiological alarm conditions, yieldinggreater accuracy in predicting imminent incapacitation before it hasprogressed to the point where a user is unable to act to prevent it.

Referring now to FIG. 9, an embodiment of device 100 in use as a devicefor training pilots using physiological sensor feedback for flightcircumstances that cause hypoxemia is illustrated. Device 100 may beincorporated in a system 900 for training pilots using physiologicalsensor feedback. Device 100 may be any device as disclosed above; deviceincludes a training and feedback processor 120, which may include anytraining and feedback processor 120 as described above in reference toFIGS. 1-8. Training and feedback processor 120 is in communication withat least a physiological sensor 116, which may include any physiologicalsensor as described above in reference to FIGS. 1-8. Device 100 mayinclude and/or communicate with a user signaling device 128, which mayinclude any user signaling device 128 as described above in reference toFIGS. 1-8. Device may include a memory 904, which may be a solid-statememory or the like; memory 904 may be used to record data during testperiods, sorties, simulations, and the like, for instance as describedabove in reference to FIGS. 1-8. Device 100 may include a power source908, which may include without limitation a local power storage devicesuch as a battery or fuel cell.

Continuing to refer to FIG. 9, and as further described above inreference to FIGS. 1-8, device may include a housing 104. Housing may beconfigured to be mounted to a pilot 912 or other user to be trained orregarding whom data is to be gathered; it should be understood thatpilot 912 is illustrated here only to indicate a manner in which device100 interacts with a user and does not imply that pilot 912 is a part ofsystem 900 and/or device 100. Housing may be mounted to pilot 912 orother user as described above in reference to FIGS. 1-8. For instance,and without limitation, housing may be mounted so as to place at least aphysiological sensor 116 in contact with a locus on pilot 912 and/orother user as described above in reference to FIGS. 1-8.

Still viewing FIG. 9, device 100 may communicate at times with anexternal device 916; communication may be continuous or episodic. Forinstance, and as described above in reference to FIGS. 1-8, device 100may communicate with external device 916 at the end of a sortie,simulation, or testing period to provide data collected during thesortie, simulation, or testing period; alternatively or additionally,device 100 may communicate continuously with external device 916 duringat least a portion of sortie, simulation, and/or testing period, forinstance to provide information to a person coordinating the sortie,simulation, or testing period, such as a commanding officer or the like.External device 916 may alternatively or additionally include a deviceincorporated in a simulation environment, vehicle, aircraft, or thelike. System 900 may include or communicate with an external display920. For instance, and without limitation external device 916 mayprovide information to an external display 920 including a monitor,audio communication device, or the like to a commanding officer, personrecording a simulation, or the like. External display 920 may include avehicular display as described above; vehicular display may receiveinformation from user signaling device 128 and/or other components ofdevice 100 to provide information to user and/or pilot 912. Data may berelayed from external device 916 to further memory devices and/orsystems such as without limitation cloud storage 924; data may beanalyzed in combination with additional data captured from pilot 912 orother user, for instance during other sorties, simulations, or testperiods, from additional users, or the like, and may be analyzed asdescribed above to detect relationships between data detected byphysiological sensors and/or environmental sensors as described above.Any relationship between any element of data captured by one or morephysiological sensors, any element of data captured by one or moreenvironmental sensors, and/or any element of data concerning a flightcircumstance as described in further detail below, may be analyzed,calculated, and/or determined using machine learning and/or dataanalysis as described above.

Still referring to FIG. 9, device 100 may be installed in, and/or system900 may include, a flight condition generating device 928. Flightcondition generating device 928 as used herein includes any device thatalters environmental parameters in a manner consistent with alternationsthat may be encountered during circumstances for which a user may betrained, including conditions likely to occur during a flight. Suchconditions may include variations in atmospheric and/or respiratoroxygen, variations in temperature, variations in barometric pressure,variations in acceleration and/or G forces, or the like. Flightcondition generating device 928 may include a chamber and/or device inwhich oxygen levels and/or barometric pressure may be adjusted such aswithout limitation a Reduced Oxygen Breathing Device (ROBD), acentrifuge or other device that varies G forces experienced by a user, aflight simulator, and/or an aircraft, including an aircraft the userand/or pilot 912 is being trained to use.

Referring now to FIG. 10, an exemplary embodiment of a method 1000 oftraining pilots using physiological sensor feedback for flightcircumstances that cause hypoxemia is illustrated. At step 1005, adevice 100 for physiological sensor feedback is mounted to a user; usermay be a pilot 912. Device 100 includes a housing 104 at least aphysiological sensor attached to the housing and configured to detect atleast a physiological parameter associated with hypoxemia 116 and atraining and feedback processor 120 in communication with the at least aphysiological sensor 116, as described above in reference to FIGS. 1-8.Mounting device 100 to user may be performed according to any process orprocess steps as described above in reference to FIGS. 1-8.

At step 1010, and still referring to FIG. 10, training and feedbackprocessor 120 detects at least a flight condition having a causativeassociation with hypoxemia. A flight condition, as used herein, is anyset of circumstances in an aircraft, flight simulator, or other flightcondition generating device 928; at least a flight condition may includeany state of environment or modification to environment within a flightcondition generating device 928 that flight condition generating device928 is commanded by a person or system to perform, including a change inair pressure, oxygen content, acceleration, direction, rotational orangular velocity, barometric pressure, variations in temperature, or thelike. At least a flight condition may include any condition detectableusing at least an environmental sensor 124. At least a flight conditionhaving a causative association with hypoxemia may include anycircumstance in a flight and/or flight simulation tending to causeeither generalized or cranial/cerebral hypoxemia, including withoutlimitation high G-forces imposed by acceleration of an aircraft, motionof a centrifuge, or the like, low atmospheric and/or respirator oxygencontents, low barometric pressure, and the like. Data analysis and/ormachine learning as described above may be used to detect relationshipsbetween flight conditions and hypoxemia.

Still referring to FIG. 10, training and training and feedback processor120 may detect the at least a flight condition by receiving dataindicating a flight condition that a flight condition generating device928 is generating from the flight condition generating device 928. Forinstance, a device, such as an ROBD or the like, that adjustsatmospheric oxygen levels and/or barometric pressure experienced by apilot 912 may receive and/or automatically generate a command to adjustoxygen level and/or barometric pressure; the command may be transmittedand/or otherwise provided to training and training and feedbackprocessor 120 as a flight condition. As a further example, where flightcondition generating device 928 is a device that varies G forces on auser, such as a centrifuge, flight condition generating device 928 mayreceive or automatically generate a command to increase and/or decreaseG forces on user, such as a command to increase and/or decrease angularvelocity of a centrifuge; this command may be transmitted or otherwiseprovided to training and feedback processor 120 as a flight condition.Where flight condition generating device 928, one or more commands frompilot 912, autopilot guidance computer or instrumentation, or the likemay be provided to training and feedback processor 120; for instance,pilot manual controls in a fly-by-wire or partial fly-by-wire aircraftmay take the form of electronic signals, which may also be transmittedand/or provided to training and feedback processor 120. Flight plan orprecalculated trajectory data may be provided to training and feedbackprocessor 120 as part of data describing at least a flight condition;for instance, a fly-by-wire system may be programmed to respond to aparticular pilot and/or autopilot command by causing an aircraft totraverse a certain trajectory at a certain velocity or with a certainacceleration.

Continuing to refer to FIG. 10, training and training and feedbackprocessor 120 may detect at least a flight condition using at least anenvironmental sensor 124. Detection may be performed according to anyprocess described above for detection of environmental parameters usingat least an environmental sensor 124 that is part of device 100 orexternal to device 100 and in communication with device 100. Forinstance, and without limitation, an oxygen sensor may detect an oxygenlevel, a temperature sensor may detect a temperature level, a barometricpressure sensor may detect a barometric pressure level, and a motionsensor may detect G forces, acceleration.

Still referring to FIG. 10, detection of at least a flight condition mayinclude a combination of receiving data from a flight conditiongenerating device 928 and detection using at least an environmentalsensor 124. For instance pilot 912 and/or autopilot may direct anaircraft to climb to a certain altitude at a certain velocity, which maybe provided to training and feedback processor 120, while motion,oxygen, and/or pressure sensors may detect actual conditions, which mayvary from expected conditions.

At step 1015, training and training and feedback processor 120 measuresat least a physiological parameter associated with hypoxemia using atleast a physiological sensor 116. Measuring may include measuring atleast a hematological parameter. At least a hematological parameter mayinclude a heart rate. At least a hematological parameter may include ablood oxygen level. At least a physiological parameter may include twoor more hematological parameters; for instance, and as described infurther detail above, at least a physiological parameter may include acombination of heart rate and blood oxygen saturation. For instance,changes to heart rate and changes in blood oxygen saturation may bedetected concurrently or at temporally proximate points, as described infurther detail above in reference to FIGS. 1-8.

At step 1020, and still referring to FIG. 10, training and feedbackprocessor 120 determines a degree of pilot hypoxemia based on thephysiological parameter. For instance, where measuring includesmeasuring at least a hematological parameter determining may includedetermining the at least a hematological parameter is associated withthe level of hypoxemia; this may be accomplished, without limitation, asdescribed above. For instance, where measuring includes measuring ablood oxygen level, determining may include determining that thedetected blood oxygen level is associated with the level of hypoxemia.This may be performed according to thresholds indicating levels ofprobable degrees of impairment associated with various percentages ofblood oxygen saturation as described above; thresholds may includedefault thresholds set by factory or according to typical users, and/orthresholds set according to user values, for instance using changes todefault thresholds as directed by data collected concerning user. As afurther non-limiting example, where the at least a hematologicalparameter includes a heart rate, determining may include determiningthat the detected heart rate is associated with a level of hypoxemia;for instance and without limitation, an increase in heart rate, a changein blood pressure, or the like may indicate a likely movement from onethreshold to another regarding blood oxygen saturation levels. Wheremeasuring includes measuring a heart rate and a blood oxygen level,which may be a blood oxygen saturation level, determination may includedetermining that a combination of blood oxygen level and heart rate isassociated with the level of hypoxemia; this may be performed asdescribed above in reference to FIGS. 1-8.

Still referring to FIG. 10, degree of hypoxemia may include anon-impairing degree of hypoxemia as described above; for instance,degree of hypoxemia may meet a threshold for a “possible problem,” whichmay also serve as an indication that blood oxygen condition of pilot 912may be likely to deteriorate further. Degree of hypoxemia may include animpairing degree of hypoxemia; an impairing degree of hypoxemia may, forinstance, relate to a second threshold as described above, for“performance degraded.” Degree of hypoxemia may include a degree ofhypoxemia associated with an imminent loss of consciousness. Degree ofhypoxemia may be determined by relationships between detected factorsand/or physiological parameters. For instance, and without limitation, adecrease in blood oxygen saturation of 5% by itself may not suffice totrip a threshold based on blood oxygen saturation alone, but aconcomitant increase in heart rate or decrease in blood pressure maycause training and feedback processor 120 to determine that pilot 912has arrived at a higher or more severe degree of hypoxemia. As a furthernon-limiting example, one or more factors detected using at least aphysiological sensor 116 and/or at least an environmental sensor 124 maycause training and feedback processor 120 to treat a given hematologicalor other parameter as indicating a more or less severe degree ofhypoxemia; such factors may include, without limitation, (1) detectionof a degree of hydration of the pilot 912, where a lower degree ofhydration may be associated with more acute hypoxemia for a given bloodoxygen saturation level and/or heart rate; (2) a degree of pilot fatigueas determined, for instance, by brain wave activity, history or lengthof recent activity, or the like, and where a higher degree of fatigue orgreater amount of recent flight activity may be associated with a moresevere level of hypoxemia for a given blood oxygen saturation percentageand/or heart rate; (3) detected changes in neural oscillations, where,for instance, change indicating a tendency toward drowsiness, and orindication of entry into early stages of sleep or the like, wheregreater drowsiness and/or incipient hypnagogic states may indicate ahigher degree of hypoxemia for a given blood oxygen saturation leveland/or heart rate; (4) detected changes in ketone or VOC emission byuser, where greater ketone and/or VOC emission indicates a higher degreeof fatigue, which may be used as described above, and/or a more severedegree of hypoxemia for a given blood oxygen saturation level and/orheart rate; and/or (5) temperature, where a temperature significantlyhigher or lower than room temperature may be associated with a moresevere degree of hypoxemia for a given blood oxygen saturationpercentage and/or heart rate. Each such factor, or any combinationthereof, may also be associated by training and feedback processor 120with a greater or lesser projected rate of degradation of pilot's degreeof hypoxemia; for instance, a more fatigued pilot, or less hydratedpilot, may be more likely to descend from a current level of hypoxemiato a worse level than a well-rested or adequately hydrated pilot. Acumulative fatigue model may be generated or applied to determine adegree to which pilot fatigue affects either a current level ofhypoxemia or a likely future rate of degradation. Degree of hypoxemiamay include a degree of generalized or systemic hypoxemia, and/or adegree of cerebral and/or cranial hypoxemia.

At step 1025, and continuing to refer to FIG. 10, method 1000 includesindicating using a user-signaling device 128, degree of pilot hypoxemiato at least a user. At least a user may include pilot 912; for instance,and as described in further detail above, an alarm may be transmitted topilot via user-signaling device 128, including without limitationthrough a bone-conducting transducer or other alarm signal, a vehiculardisplay, or the like. At least a use may include a person who is notpilot 912, such as a commanding officer, a person administering a testor training session, or the like. Indication may include an instructionor recommendation to act to alleviate conditions that may be causing adegree of hypoxemia; for instance, instruction or recommendation mayinstruct or recommend a modification to motion being undertaken byflight condition generating device 928 to decrease G forces on the pilot912, a recommendation to increase oxygen levels and/or air pressure inan ROBD or similar device, a recommendation to decrease altitude of anaircraft, or the like. In an embodiment, training and feedback processor120 may transmit an instruction to a flight condition generating device928 to change the flight condition; flight condition generating device928 may, for instance, automatically reduce G forces or increase airpressure or oxygen levels

With continued reference to FIG. 10, training and feedback processor 120generates at least a pilot-specific flight guideline using the at leasta flight condition and the level of hypoxemia. Generation of at least apilot-specific flight guideline may include determining an associationbetween at least a physiological condition, at least a flight condition,and/or other information concerning pilot and/or other user. At least apilot-specific flight guideline may be based on baseline data regardingpilot 912, on one or more training or mission goals, or both. Forinstance, a goal of a training session may be for a pilot 912 to operateunder light (e.g., relating to a first threshold level as describedabove) to moderate (e.g., relating to a second threshold level asdescribed above) hypoxemia, for a certain period of time intended, forinstance, to indicate circumstances under which a mission-critical orotherwise important maneuver or act must be performed at high altitudes,high speeds, or other circumstances likely to induce at least a degreeof hypoxemia; length of period and/or degree of hypoxemia experiencedmay be set according to pilot's record of past performance, baselinesrecorded regarding that pilot's performance under light to moderatehypoxemia and/or that pilot's tendency to degrade to higher degrees ofhypoxemia under some circumstances, or the like. Another goal may, forinstance be to have pilot 912 undergo a particular environmentalcondition, such as atmospheric oxygen below a set level and/or a seriesof high-G maneuvers and/or periods, and to attempt and/or practicestrategies for avoiding incapacitation. A second instruction may issue,as well; for instance, if pilot 912 is degrading more than expected, atraining session may be modified to be less severe or aborted. At leasta pilot-specific flight guideline may be provided to at least a userand/or a flight condition generation device 928 as an instruction, asdescribed above. As noted above, any data regarding past pilotperformance, baselines, and the like, together with correlatedphysiological parameters, environmental parameters, and/or flightconditions as described above may be analyzed using data analysis and/ormachine learning as described above, to derive mathematicalrelationships between various factors; such relationships can be used toset thresholds, for instance as described above, and to plan pilottraining and/or missions to remain within certain threshold ranges, toincrease pilot resistance to hypoxemia and extend such threshold ranges,or the like. In an embodiment, both device 100 and pilot may learn ineach mission and/or training session to work more effectively within thephysiological limits of the pilot, enabling a greater range of actionsto be performed to a higher degree of safety. Methods as describedherein and/or device 100 may enable training profiles to identifypotential shortfalls and/or difficulties, for instance by modifyingtraining profiles and/or plans to avoid detected episodes of hypoxemia,either for particular pilots 912, for particular cohorts or demographicsets of pilots, or for pilots in general.

Although methods, devices, and systems have been described above fortraining pilots for circumstances that may involve hypoxemia,embodiments described above may similarly be used to train other personsfor other situations likely to involve and/or induce hypoxemia; flightcondition may, in other words, be replaced by a mission condition and/orother condition specific to a particular situation. Such alternativesmay include training for astronauts/cosmonauts, firefighters, divers,mountaineers, athletes, or the like.

It is to be noted that any one or more of the aspects and embodimentsdescribed herein may be conveniently implemented using one or moremachines (e.g., one or more computing devices that are utilized as auser computing device for an electronic document, one or more serverdevices, such as a document server, etc.) programmed according to theteachings of the present specification, as will be apparent to those ofordinary skill in the computer art. Appropriate software coding canreadily be prepared by skilled programmers based on the teachings of thepresent disclosure, as will be apparent to those of ordinary skill inthe software art. Aspects and implementations discussed above employingsoftware and/or software modules may also include appropriate hardwarefor assisting in the implementation of the machine executableinstructions of the software and/or software module.

Such software may be a computer program product that employs amachine-readable storage medium. A machine-readable storage medium maybe any medium that is capable of storing and/or encoding a sequence ofinstructions for execution by a machine (e.g., a computing device) andthat causes the machine to perform any one of the methodologies and/orembodiments described herein. Examples of a machine-readable storagemedium include, but are not limited to, a magnetic disk, an optical disc(e.g., CD, CD-R, DVD, DVD-R, etc.), a magneto-optical disk, a read-onlymemory “ROM” device, a random access memory “RAM” device, a magneticcard, an optical card, a solid-state memory device, an EPROM, an EEPROM,and any combinations thereof. A machine-readable medium, as used herein,is intended to include a single medium as well as a collection ofphysically separate media, such as, for example, a collection of compactdiscs or one or more hard disk drives in combination with a computermemory. As used herein, a machine-readable storage medium does notinclude transitory forms of signal transmission.

Such software may also include information (e.g., data) carried as adata signal on a data carrier, such as a carrier wave. For example,machine-executable information may be included as a data-carrying signalembodied in a data carrier in which the signal encodes a sequence ofinstruction, or portion thereof, for execution by a machine (e.g., acomputing device) and any related information (e.g., data structures anddata) that causes the machine to perform any one of the methodologiesand/or embodiments described herein.

Examples of a computing device include, but are not limited to, anelectronic book reading device, a computer workstation, a terminalcomputer, a server computer, a handheld device (e.g., a tablet computer,a smartphone, etc.), a web appliance, a network router, a networkswitch, a network bridge, any machine capable of executing a sequence ofinstructions that specify an action to be taken by that machine, and anycombinations thereof. In one example, a computing device may includeand/or be included in a kiosk.

FIG. 11 shows a diagrammatic representation of one embodiment of acomputing device in the exemplary form of a computer system 1100 withinwhich a set of instructions for causing a control system, such as thedevice 100 disclosed above, to perform any one or more of the aspectsand/or methodologies of the present disclosure may be executed. It isalso contemplated that multiple computing devices may be utilized toimplement a specially configured set of instructions for causing one ormore of the devices to perform any one or more of the aspects and/ormethodologies of the present disclosure. Computer system 1100 includes aprocessor 1104 and a memory 1108 that communicate with each other, andwith other components, via a bus 1112. Bus 1112 may include any ofseveral types of bus structures including, but not limited to, a memorybus, a memory controller, a peripheral bus, a local bus, and anycombinations thereof, using any of a variety of bus architectures.

Memory 1108 may include various components (e.g., machine-readablemedia) including, but not limited to, a random-access memory component,a read only component, and any combinations thereof. In one example, abasic input/output system 1116 (BIOS), including basic routines thathelp to transfer information between elements within computer system1100, such as during start-up, may be stored in memory 1108. Memory 1108may also include (e.g., stored on one or more machine-readable media)instructions (e.g., software) 1120 embodying any one or more of theaspects and/or methodologies of the present disclosure. In anotherexample, memory 1108 may further include any number of program modulesincluding, but not limited to, an operating system, one or moreapplication programs, other program modules, program data, and anycombinations thereof.

Computer system 1100 may also include a storage device 1124. Examples ofa storage device (e.g., storage device 1124) include, but are notlimited to, a hard disk drive, a magnetic disk drive, an optical discdrive in combination with an optical medium, a solid-state memorydevice, and any combinations thereof. Storage device 1124 may beconnected to bus 1112 by an appropriate interface (not shown). Exampleinterfaces include, but are not limited to, SCSI, advanced technologyattachment (ATA), serial ATA, universal serial bus (USB), IEEE 1394(FIREWIRE), and any combinations thereof. In one example, storage device1124 (or one or more components thereof) may be removably interfacedwith computer system 1100 (e.g., via an external port connector (notshown)). Particularly, storage device 1124 and an associatedmachine-readable medium 1128 may provide nonvolatile and/or volatilestorage of machine-readable instructions, data structures, programmodules, and/or other data for computer system 1100. In one example,software 1120 may reside, completely or partially, withinmachine-readable medium 1128. In another example, software 1120 mayreside, completely or partially, within processor 1104.

Computer system 1100 may also include an input device 1132. In oneexample, a user of computer system 1100 may enter commands and/or otherinformation into computer system 1100 via input device 1132. Examples ofan input device 1132 include, but are not limited to, an alpha-numericinput device (e.g., a keyboard), a pointing device, a joystick, agamepad, an audio input device (e.g., a microphone, a voice responsesystem, etc.), a cursor control device (e.g., a mouse), a touchpad, anoptical scanner, a video capture device (e.g., a still camera, a videocamera), a touchscreen, and any combinations thereof. Input device 1132may be interfaced to bus 1112 via any of a variety of interfaces (notshown) including, but not limited to, a serial interface, a parallelinterface, a game port, a USB interface, a FIREWIRE interface, a directinterface to bus 1112, and any combinations thereof. Input device 1132may include a touch screen interface that may be a part of or separatefrom display 1136, discussed further below. Input device 1132 may beutilized as a user selection device for selecting one or more graphicalrepresentations in a graphical interface as described above.

A user may also input commands and/or other information to computersystem 1100 via storage device 1124 (e.g., a removable disk drive, aflash drive, etc.) and/or network interface device 1140. A networkinterface device, such as network interface device 1140, may be utilizedfor connecting computer system 1100 to one or more of a variety ofnetworks, such as network 1144, and one or more remote devices 1148connected thereto. Examples of a network interface device include, butare not limited to, a network interface card (e.g., a mobile networkinterface card, a LAN card), a modem, and any combination thereof.Examples of a network include, but are not limited to, a wide areanetwork (e.g., the Internet, an enterprise network), a local areanetwork (e.g., a network associated with an office, a building, a campusor other relatively small geographic space), a telephone network, a datanetwork associated with a telephone/voice provider (e.g., a mobilecommunications provider data and/or voice network), a direct connectionbetween two computing devices, and any combinations thereof. A network,such as network 1144, may employ a wired and/or a wireless mode ofcommunication. In general, any network topology may be used. Information(e.g., data, software 1120, etc.) may be communicated to and/or fromcomputer system 1100 via network interface device 1140.

Computer system 1100 may further include a video display adapter 1152for communicating a displayable image to a display device, such asdisplay device 1136. Examples of a display device include, but are notlimited to, a liquid crystal display (LCD), a cathode ray tube (CRT), aplasma display, a light emitting diode (LED) display, and anycombinations thereof. Display adapter 1152 and display device 1136 maybe utilized in combination with processor 1104 to provide graphicalrepresentations of aspects of the present disclosure. In addition to adisplay device, computer system 1100 may include one or more otherperipheral output devices including, but not limited to, an audiospeaker, a printer, and any combinations thereof. Such peripheral outputdevices may be connected to bus 1112 via a peripheral interface 1156.Examples of a peripheral interface include, but are not limited to, aserial port, a USB connection, a FIREWIRE connection, a parallelconnection, and any combinations thereof.

The foregoing has been a detailed description of illustrativeembodiments of the invention. Various modifications and additions can bemade without departing from the spirit and scope of this invention.Features of each of the various embodiments described above may becombined with features of other described embodiments as appropriate inorder to provide a multiplicity of feature combinations in associatednew embodiments. Furthermore, while the foregoing describes a number ofseparate embodiments, what has been described herein is merelyillustrative of the application of the principles of the presentinvention. Additionally, although particular methods herein may beillustrated and/or described as being performed in a specific order, theordering is highly variable within ordinary skill to achieve methods,systems, devices and/or software according to the present disclosure.Accordingly, this description is meant to be taken only by way ofexample, and not to otherwise limit the scope of this invention.

Exemplary embodiments have been disclosed above and illustrated in theaccompanying drawings. It will be understood by those skilled in the artthat various changes, omissions and additions may be made to that whichis specifically disclosed herein without departing from the spirit andscope of the present invention.

What is claimed is:
 1. A device for training pilots using physiologicalsensor feedback for flight circumstances that cause hypoxemia, thedevice comprising: a housing configured to be mounted to an exteriorbody surface of a user; at least a physiological sensor attached to thehousing and configured to detect at least a physiological parameterassociated with hypoxemia; and a training and feedback processor incommunication with the at least a physiological sensor, the training andfeedback processor designed and configured to: detect at least a flightcondition having a causative association with hypoxemia; measure, usingthe at least a physiological sensor, at least a physiological parameterassociated with hypoxemia; determine, by the training and feedbackprocessor, and based on the at least a physiological parameter, a degreeof pilot hypoxemia; determine a training goal associated with hypoxemia;and generate a pilot-specific flight guideline based upon the degree ofpilot hypoxemia and the training goal associated with hypoxemia; and auser signaling device in communication with the training and feedbackprocessor, the user signaling device configured to indicate the degreeof pilot hypoxemia to at least a user.
 2. The device of claim 1, whereinthe at least a physiological sensor further comprises a heart-ratesensor.
 3. The device of claim 1, wherein the at least a physiologicalsensor further comprises a blood oxygen sensor.
 4. The device of claim1, wherein the at least a physiological sensor is configured to detectat least a hematological parameter of at least a branch of a carotidartery.
 5. The device of claim 4, wherein the housing is furtherconfigured to place the at least a physiological sensor in proximity tothe at least a branch of the carotid artery.
 6. The device of claim 1further comprising at least an environmental sensor.
 7. The device ofclaim 6, wherein the at least an environmental sensor includes at leasta motion sensor.
 8. The device of claim 6, wherein the at least anenvironmental sensor includes at least atmospheric oxygen sensor.
 9. Thedevice of claim 6, wherein the at least an environmental sensor includesat least a barometric sensor.
 10. A method of training pilots usingphysiological sensor feedback for flight circumstances that causehypoxemia, the method comprising: mounting a device for physiologicalsensor feedback to a user, wherein the device further comprises ahousing, at least a physiological sensor attached to the housing andconfigured to detect at least a physiological parameter associated withhypoxemia, and a training and feedback processor in communication withthe at least a physiological sensor; detecting, by the training andfeedback processor, at least a flight condition having a causativeassociation with hypoxemia; measuring, using the at least aphysiological sensor at least a physiological parameter associated withhypoxemia; determining, by the training and feedback processor, andbased on the at least a physiological parameter, a degree of pilothypoxemia; determining, by the training and feedback processor, atraining goal associated with hypoxemia; generating a pilot-specificflight guideline based upon the degree of pilot hypoxemia and thetraining goal associated with hypoxemia; and indicating, using a usersignaling device, the degree of pilot hypoxemia to at least a user. 11.The method of claim 10, wherein detection of the at least a flightcondition further comprises receiving, from a flight conditiongenerating device, data indicating a flight condition.
 12. The method ofclaim 10, wherein detection includes detection of the at least a flightcondition using at least an environmental sensor.
 13. The method ofclaim 10, wherein: measuring includes measuring at least a hematologicalparameter; and determining further comprises determining the at least ahematological parameter is associated with the degree of pilothypoxemia.
 14. The method of claim 13, wherein the at least ahematological parameter further comprises a heart rate.
 15. The methodof claim 10 wherein: measuring includes measuring a blood oxygen level;and determining further comprises determining that the blood oxygenlevel is associated with the degree of pilot hypoxemia.
 16. The methodof claim 15, wherein: measuring further comprises measuring a heartrate; and determination further comprises determining that a combinationof blood oxygen level and heart rate is associated with the degree ofpilot hypoxemia.
 17. The method of claim 10, wherein the degree of pilothypoxemia further comprises a non-impairing degree of hypoxemia.
 18. Themethod of claim 10, wherein the degree of pilot hypoxemia furthercomprises an impairing degree of hypoxemia.
 19. The method of claim 10,wherein the degree of pilot hypoxemia further comprises a degree ofhypoxia associated with an imminent loss of consciousness.
 20. Themethod of claim 10, wherein the training goal is further associated witha duration of hypoxemia and wherein pilot-specific flight guideline isgenerated further based upon the duration of hypoxemia.